{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T06:57:18Z","timestamp":1773903438909,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T00:00:00Z","timestamp":1725408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Key R&amp;D Program of Hubei","award":["2022BCA080"],"award-info":[{"award-number":["2022BCA080"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The distribution and development of rock mass discontinuities in 3D space control the deformation and failure characteristics of the rock mass, which in turn affect the strength, permeability, and stability of rock masses. Therefore, it is essential to accurately and efficiently characterize these discontinuities. Light Detection and Ranging (LiDAR) now allows for fast and precise 3D data collection, which supports the creation of new methods for characterizing rock mass discontinuities. However, uneven density distribution and local surface undulations can limit the accuracy of discontinuity characterization. To address this, we propose a method for characterizing complex rock mass discontinuities based on laser point cloud data. This method is capable of processing datasets with varying densities and can reduce over-segmentation in non-planar areas. The suggested approach involves a five-stage process that includes: (1) adaptive resampling of point cloud data based on density comparison; (2) normal vector calculation using Principal Component Analysis (PCA); (3) identifying non-planar areas using a watershed-like algorithm, and determine the main discontinuity sets using Multi-threshold Mean Shift (MTMS); (4) identify single discontinuity clusters using Density-Based Spatial Clustering of Applications with Noise (DBSCAN); (5) fitting discontinuity planes with Random Sample Consensus (RANSAC) and determining discontinuity orientations using analytic geometry. This method was applied to three rock slope datasets and compared with previous research results and manual measurement results. The results indicate that this method can effectively reduce over-segmentation and the characterization results have high accuracy.<\/jats:p>","DOI":"10.3390\/rs16173291","type":"journal-article","created":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T08:46:22Z","timestamp":1725439582000},"page":"3291","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Characterization of Complex Rock Mass Discontinuities from LiDAR Point Clouds"],"prefix":"10.3390","volume":"16","author":[{"given":"Yanan","family":"Liu","sequence":"first","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Weihua","family":"Hua","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7250-8781","authenticated-orcid":false,"given":"Qihao","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0045-9642","authenticated-orcid":false,"given":"Xiuguo","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"B30","DOI":"10.1115\/1.1451165","article-title":"Engineering Rock Mechanics: An Introduction to the Principles","volume":"55","author":"Hudson","year":"2002","journal-title":"Appl. Mech. Rev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"5137","DOI":"10.1007\/s00603-019-01851-3","article-title":"Investigating Hydraulic Fracturing Complexity in Naturally Fractured Rock Masses Using Fully Coupled Multiscale Numerical Modeling","volume":"52","author":"Zhang","year":"2019","journal-title":"Rock. Mech. Rock. Eng."},{"key":"ref_3","first-page":"319","article-title":"Suggested methods for the quantitative description of discontinuities in rock masses","volume":"15","author":"Barton","year":"1978","journal-title":"ISRM Congr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.enggeo.2009.03.004","article-title":"Close-range terrestrial digital photogrammetry and terrestrial laser scanning for discontinuity characterization on rock cuts","volume":"106","author":"Sturzenegger","year":"2009","journal-title":"Eng. Geol."},{"key":"ref_5","unstructured":"Goodman, R.E., and Shi, G.-H. (1985). Block Theory and Its Application to Rock Engineering, Springer."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.ijrmms.2008.06.003","article-title":"Rock slope stability assessment through rock mass classification systems","volume":"46","author":"Pantelidis","year":"2009","journal-title":"Int. J. Rock. Mech. Min. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.ijrmms.2010.06.013","article-title":"Comparison of limit-equilibrium, numerical and physical models of wall slope stability","volume":"48","author":"Alejano","year":"2011","journal-title":"Int. J. Rock. Mech. Min. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"932","DOI":"10.1016\/j.ijrmms.2011.04.010","article-title":"3D laser imaging for joint orientation analysis","volume":"48","author":"Mah","year":"2011","journal-title":"Int. J. Rock. Mech. Min. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1002\/esp.3493","article-title":"Terrestrial laser scanning of rock slope instabilities. Earth Surf","volume":"39","author":"Oppikofer","year":"2014","journal-title":"Process. Landf."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"487","DOI":"10.5194\/se-10-487-2019","article-title":"How do we see fractures? Quantifying subjective bias in fracture data collection","volume":"10","author":"Andrews","year":"2019","journal-title":"Solid. Earth"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Pagano, M., Palma, B., Ruocco, A., and Parise, M. (2020). Discontinuity Characterization of Rock Masses through Terrestrial Laser Scanner and Unmanned Aerial Vehicle Techniques Aimed at Slope Stability Assessment. Appl. Sci., 10.","DOI":"10.3390\/app10082960"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3005","DOI":"10.1007\/s00603-018-1519-9","article-title":"Automatic Mapping of Discontinuity Persistence on Rock Masses Using 3D Point Clouds. Rock Mech","volume":"51","author":"Riquelme","year":"2018","journal-title":"Rock. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"106232","DOI":"10.1016\/j.enggeo.2021.106232","article-title":"Towards semi-automatic discontinuity characterization in rock tunnel faces using 3D point clouds","volume":"291","author":"Chen","year":"2021","journal-title":"Eng. Geol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1016\/j.jrmge.2019.10.006","article-title":"A modified method of discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces","volume":"12","author":"Zhang","year":"2020","journal-title":"J. Rock. Mech. Geotech. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2195","DOI":"10.1002\/gj.4708","article-title":"An efficient adaptive approach to automatically identify rock discontinuity parameters using 3D point cloud model from outcrops","volume":"58","author":"Cai","year":"2023","journal-title":"Geol. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"106615","DOI":"10.1016\/j.enggeo.2022.106615","article-title":"Automatic classification and mapping of the seabed using airborne LiDAR bathymetry","volume":"301","author":"Janowski","year":"2022","journal-title":"Eng. Geol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"106851","DOI":"10.1016\/j.enggeo.2022.106851","article-title":"Intelligent scanning for optimal rock discontinuity sets considering multiple parameters based on manifold learning combined with UAV photogrammetry","volume":"309","author":"Liu","year":"2022","journal-title":"Eng. Geol."},{"key":"ref_18","first-page":"254","article-title":"Lessons learned from the application of UAV-enabled structure-from-motion photogrammetry in geotechnical engineering","volume":"4","author":"Zekkos","year":"2018","journal-title":"Int. J. Geoengin. Case Hist."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2027","DOI":"10.1007\/s10346-020-01416-4","article-title":"UAVs for monitoring, investigation, and mitigation design of a rock slope with multiple failure mechanisms\u2014A case study","volume":"17","author":"Rodriguez","year":"2020","journal-title":"Landslides"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3376","DOI":"10.1007\/s11629-023-7914-z","article-title":"Structural plane recognition from three-dimensional laser scanning points using an improved region-growing algorithm based on the robust randomized Hough transform","volume":"20","author":"Xu","year":"2023","journal-title":"J. Mt. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1705","DOI":"10.1007\/s00603-021-02748-w","article-title":"Rock Discontinuities Identification from 3D Point Clouds Using Artificial Neural Network","volume":"55","author":"Ge","year":"2022","journal-title":"Rock Mech. Rock. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"105603","DOI":"10.1016\/j.ijrmms.2023.105603","article-title":"A computationally efficient approach to automatically extract rock mass discontinuities from 3D point cloud data","volume":"172","author":"Daghigh","year":"2023","journal-title":"Int. J. Rock. Mech. Min. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1007\/s10064-022-02994-4","article-title":"Application of photogrammetry and in-situ test technology in the stability evaluation of gangue dump slope","volume":"82","author":"Liu","year":"2022","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Cirillo, D., Zappa, M., Tangari, A.C., Brozzetti, F., and Ietto, F. (2024). Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area. Drones, 8.","DOI":"10.3390\/drones8010031"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"105442","DOI":"10.1016\/j.enggeo.2019.105442","article-title":"Automatic identification and characterization of discontinuities in rock masses from 3D point clouds","volume":"265","author":"Kong","year":"2020","journal-title":"Eng. Geol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.gr.2024.04.017","article-title":"An unsupervised method for rock discontinuities rapid characterization from 3D point clouds under noise","volume":"132","author":"Chen","year":"2024","journal-title":"Gondwana Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.enggeo.2018.05.007","article-title":"Automated measurements of discontinuity geometric properties from a 3D-point cloud based on a modified region growing algorithm","volume":"242","author":"Ge","year":"2018","journal-title":"Eng. Geol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1007\/s00603-007-0155-6","article-title":"Fuzzy spectral clustering for identification of rock discontinuity sets","volume":"41","author":"Jimenez","year":"2008","journal-title":"Rock. Mech. Rock. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.jsg.2014.05.014","article-title":"Surveying and modeling of rock discontinuities by terrestrial laser scanning and photogrammetry: Semi-automatic approaches for linear outcrop inspection","volume":"66","author":"Assali","year":"2014","journal-title":"J. Struct. Geol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.ijrmms.2012.06.003","article-title":"Automated mapping of rock discontinuities in 3D lidar and photogrammetry models","volume":"54","author":"Lato","year":"2012","journal-title":"Int. J. Rock. Mech. Min. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.enggeo.2013.07.008","article-title":"Automated rockmass discontinuity mapping from 3-dimensional surface data","volume":"164","author":"Lato","year":"2013","journal-title":"Eng. Geol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1177\/0361198105191300118","article-title":"Method for automated discontinuity analysis of rock slopes with three-dimensional laser scanning","volume":"1913","author":"Slob","year":"2005","journal-title":"Transp. Res. Rec."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1130\/GES00139.1","article-title":"Outcrop fracture characterization using terrestrial laser scanners: Deep-water Jackfork sandstone at Big Rock Quarry, Arkansas","volume":"4","author":"Olariu","year":"2008","journal-title":"Geosphere"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.cageo.2016.06.015","article-title":"Automatic extraction of discontinuity orientation from rock mass surface 3D point cloud","volume":"95","author":"Chen","year":"2016","journal-title":"Comput. Geosci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.cageo.2017.03.017","article-title":"Towards semi-automatic rock mass discontinuity orientation and set analysis from 3D point clouds","volume":"103","author":"Guo","year":"2017","journal-title":"Comput. Geosci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"80716","DOI":"10.1109\/ACCESS.2020.2988796","article-title":"Unsupervised K-Means Clustering Algorithm","volume":"8","author":"Sinaga","year":"2020","journal-title":"IEEE Access"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3485","DOI":"10.1007\/s11440-023-01803-w","article-title":"An efficient method for extracting and clustering rock mass discontinuities from 3D point clouds","volume":"18","author":"Yi","year":"2023","journal-title":"Acta Geotech."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Wu, W., Zhang, K., and Zhu, H. (2020). A fast automatic extraction method for rock mass discontinuity orientation using fast k-means++ and fast silhouette based on 3D point cloud. IOP Conference Series: Earth and Environmental Science, Springer.","DOI":"10.1088\/1755-1315\/570\/5\/052075"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"105241","DOI":"10.1016\/j.cageo.2022.105241","article-title":"A critical review of discontinuity plane extraction from 3D point cloud data of rock mass surfaces","volume":"169","author":"Daghigh","year":"2022","journal-title":"Comput. Geosci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1111\/phor.12145","article-title":"A multi-scale plane-detection method based on the Hough transform and region growing","volume":"31","author":"Leng","year":"2016","journal-title":"Photogramm. Rec."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1007\/s11042-019-08189-6","article-title":"Efficient and automatic plane detection approach for 3-D rock mass point clouds","volume":"79","author":"Hu","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Yu, D., Xiao, J., and Wang, Y. (2020). High-Precision Plane Detection Method for Rock-Mass Point Clouds Based on Supervoxel. Sensors, 20.","DOI":"10.3390\/s20154209"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.cageo.2012.06.014","article-title":"Rock bench: Establishing a common repository and standards for assessing rockmass characteristics using LiDAR and photogrammetry","volume":"50","author":"Lato","year":"2013","journal-title":"Comput. Geosci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1016\/j.patcog.2016.07.007","article-title":"Density-ratio based clustering for discovering clusters with varying densities","volume":"60","author":"Zhu","year":"2016","journal-title":"Pattern Recognit."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1684","DOI":"10.1109\/83.730380","article-title":"Hybrid image segmentation using watersheds and fast region merging","volume":"7","author":"Haris","year":"1998","journal-title":"IEEE Trans. Image Process."},{"key":"ref_46","unstructured":"Beucher, S. (1979, January 17\u201321). Use of watersheds in contour detection. Proceedings of the Proceedings International Workshop on Image Processing, Rennes, France."},{"key":"ref_47","unstructured":"Beucher, S. (1982, January 3\u20135). Watersheds of functions and picture segmentation. Proceedings of the ICASSP\u201982. IEEE International Conference on Acoustics, Speech, and Signal Processing, Paris, France."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1109\/TCSVT.2003.811605","article-title":"Predictive watershed: A fast watershed algorithm for video segmentation","volume":"13","author":"Chien","year":"2003","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Guo, Q., Wang, Y., Yang, S., and Xiang, Z. (2022). A method of blasted rock image segmentation based on improved watershed algorithm. Sci. Rep., 12.","DOI":"10.1038\/s41598-022-11351-0"},{"key":"ref_50","first-page":"97","article-title":"Dimensionality based scale selection in 3D lidar point clouds","volume":"38","author":"Mallet","year":"2012","journal-title":"Remote Sens. Spat. Inf. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.isprsjprs.2015.01.016","article-title":"Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers","volume":"105","author":"Weinmann","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1109\/34.87344","article-title":"Watersheds in digital spaces: An efficient algorithm based on immersion simulations","volume":"13","author":"Vincent","year":"1991","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.cageo.2014.03.014","article-title":"A new approach for semi-automatic rock mass joints recognition from 3D point clouds","volume":"68","author":"Riquelme","year":"2014","journal-title":"Comput. Geosci."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Randam sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography","volume":"24","author":"Fischer","year":"1981","journal-title":"Commun. ACM"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2022","DOI":"10.1109\/TPAMI.2012.257","article-title":"USAC: A universal framework for random sample consensus","volume":"35","author":"Raguram","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Raguram, R., Frahm, J.-M., and Pollefeys, M. (2008, January 12\u201318). A comparative analysis of RANSAC techniques leading to adaptive real-time random sample consensus. Proceedings of the Computer Vision\u2013ECCV 2008: 10th European Conference on Computer Vision, Marseille, France.","DOI":"10.1007\/978-3-540-88688-4_37"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Nguyen, A., and Le, B. (2013, January 12\u201315). 3D point cloud segmentation: A survey. Proceedings of the 2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM), Manila, Philippines.","DOI":"10.1109\/RAM.2013.6758588"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Xu, B., Jiang, W., Shan, J., Zhang, J., and Li, L. (2016). Investigation on the Weighted RANSAC Approaches for Building Roof Plane Segmentation from LiDAR Point Clouds. Remote Sens., 8.","DOI":"10.3390\/rs8010005"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1007\/s00603-008-0010-4","article-title":"Advanced Geostructural Survey Methods Applied to Rock Mass Characterization. Rock Mech","volume":"42","author":"Ferrero","year":"2009","journal-title":"Rock. Eng."},{"key":"ref_60","first-page":"qjegh2020","article-title":"Automatic extraction of rock mass discontinuity based on 3D laser scanning","volume":"54","author":"Chen","year":"2020","journal-title":"Q. J. Eng. Geol. Hydrogeol."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Liu, L., Xiao, J., and Wang, Y. (2019). Major Orientation Estimation-Based Rock Surface Extraction for 3D Rock-Mass Point Clouds. Remote Sens., 11.","DOI":"10.3390\/rs11060635"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/17\/3291\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:48:38Z","timestamp":1760111318000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/17\/3291"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,4]]},"references-count":61,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2024,9]]}},"alternative-id":["rs16173291"],"URL":"https:\/\/doi.org\/10.3390\/rs16173291","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,4]]}}}